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Spin states in semiconductors provide exceptionally stable and noise-resistant environments for qubits, positioning them as optimal candidates for reliable quantum computing technologies. The proposal to use nuclear and electronic spins of donor atoms in silicon, introduced by Kane in 1998, sparked a new research field focused on the precise positioning of individual impurity atoms for quantum devices, utilising scanning tunnelling microscopy and ion implantation. This roadmap article reviews the advancements in the 25 years since Kane's proposal, the current challenges, and the future directions in atomic-scale semiconductor device fabrication and measurement. It covers the quest to create a silicon-based quantum computer and expands to include diverse material systems and fabrication techniques, highlighting the potential for a broad range of semiconductor quantum technological applications. Key developments include phosphorus in silicon devices such as single-atom transistors, arrayed few-donor devices, one- and two-qubit gates, three-dimensional architectures, and the development of a toolbox for future quantum integrated circuits. The roadmap also explores new impurity species like arsenic and antimony for enhanced scalability and higher-dimensional spin systems, new chemistry for dopant precursors and lithographic resists, and the potential for germanium-based devices. Emerging methods, such as photon-based lithography and electron beam manipulation, are discussed for their disruptive potential. This roadmap charts the path toward scalable quantum computing and advanced semiconductor quantum technologies, emphasising the critical intersections of experiment, technological development, and theory., Comment: 94 pages

We extend the theory of the radiation pressure to include quadratic fluctuations in the position of a moving mirror. This enables the introduction of a generalized radiation pressure operator that captures higher-order effects in the mirror-field coupling. For mechanical resonators with frequencies comparable to the fundamental cavity frequency, the resulting corrections to the optomechanical Hamiltonian are quadratic in the standard radiation pressure coupling. These corrections are expected to play a significant role in the strong coupling regime of optomechanics, electromechanics, and superconducting circuit analogs., Comment: 6 pages, one figure. Extended references and general improvements. Comments are welcome

This collection of perspective pieces captures recent advancements and reflections from a dynamic research community dedicated to bridging quantum gravity, hydrodynamics, and emergent cosmology. It explores four key research areas: (a) the interplay between hydrodynamics and cosmology, including analog gravity systems; (b) phase transitions, continuum limits and emergent geometry in quantum gravity; (c) relational perspectives in gravity and quantum gravity; and (d) the emergence of cosmological models rooted in quantum gravity frameworks. Each contribution presents the distinct perspectives of its respective authors. Additionally, the introduction by the editors proposes an integrative view, suggesting how these thematic units could serve as foundational pillars for a novel theoretical cosmology framework termed "hydrodynamics on superspace"., Comment: 42 + 23 pages

In processing multiple time series, accounting for the individual features of each sequence can be challenging. To address this, modern deep learning methods for time series analysis combine a shared (global) model with local layers, specific to each time series, often implemented as learnable embeddings. Ideally, these local embeddings should encode meaningful representations of the unique dynamics of each sequence. However, when these are learned end-to-end as parameters of a forecasting model, they may end up acting as mere sequence identifiers. Shared processing blocks may then become reliant on such identifiers, limiting their transferability to new contexts. In this paper, we address this issue by investigating methods to regularize the learning of local learnable embeddings for time series processing. Specifically, we perform the first extensive empirical study on the subject and show how such regularizations consistently improve performance in widely adopted architectures. Furthermore, we show that methods preventing the co-adaptation of local and global parameters are particularly effective in this context. This hypothesis is validated by comparing several methods preventing the downstream models from relying on sequence identifiers, going as far as completely resetting the embeddings during training. The obtained results provide an important contribution to understanding the interplay between learnable local parameters and shared processing layers: a key challenge in modern time series processing models and a step toward developing effective foundation models for time series.

In ferromagnetic thin films, the presence of an out-of-plane component of the magnetic anisotropy may induce a transition from planar to stripe-like magnetic domains above a critical thickness, $t_c$. Because of the changes in the domain structure, important changes in the magnetization reversal mechanisms are observed. We present the analysis of the magnetization reversal in FePt thin films, where this phenomenon is observed, through the experimental observation of magnetic domains by magneto-optic Kerr effect microscopy. The observed reversal mechanisms are strongly dependent on the thickness of the sample. For $tt_c$, the stripe-domain structure determines the magnetization reversal.

We theoretically study stimulated and spontaneous Hawking emission from an analog horizon for spin modes in a two-component Bose-Einstein condensate, both with and without a coherent coupling between the two components. We highlight the conceptual and practical advantages that these systems offer to the experimental observation of the phenomenon, namely the massive nature of elementary excitations and the experimental accessibility of the different quadratures of the spin excitations. In particular, we go beyond the relativistic regimes previously addressed in the literature, and identify various observables that show a signature of the Hawking process, as well as additional features associated with the massive nature of the modes, such as undulations. Semi-analytical calculations of the scattering properties of the horizon and of two-point correlation functions of the emitted radiation in an ideal stationary setup are supported by time-dependent numerical simulations based on Gross-Pitaevskii and Bogoliubov theory.

In this study, we investigate the spin-charge current conversion characteristics of chemically disordered ferromagnetic single FePt thin films by spin-pumping ferromagnetic resonance experiments performed on both a resonance cavity and on patterned devices. We clearly observe a self-induced signal in a single FePt layer. The sign of a single FePt spin pumping voltage signal is consistent with a typical bilayer with a positive spin Hall angle layer such as that of Pt on top of a ferromagnet (FM), substrate//FM/Pt. Structural analysis shows a strong composition gradient due to natural oxidation at both FePt interfaces, with the Si substrate and with the air. The FePt-thickness dependence of the self-induced charge current produced allowed us to obtain $\lambda _ \text{FePt}=(1.5\pm 0.1)$ nm and self-induced $\theta_ \text{self-FePt}=0.047 \pm 0.003$, with efficiency for reciprocal effects applications $\theta _ \text{self-FePt} \times \lambda _ \text{FePt} = 0.071$ nm which is comparable to that of Pt, $\theta _ \text{SH-Pt} \times \lambda _ \text{Pt} = 0.2$ nm. Moreover, by studying bilayer systems such as Si//FePt/Pt and Si//Pt//FePt we independently could extract the individual contributions of the external inverse spin Hall effect of Pt and the self-induced inverse spin Hall effect of FePt. Notably, this method gives consistent values of charge currents produced due to only self-induced inverse spin Hall effect in FePt layers. These results advance our understanding of spin-to-charge interconversion mechanisms in composite thin films and pave the way for the development of next-generation spintronics devices based on self-torque., Comment: 13 pages, 7 figures

Smart farming and precision agriculture represent game-changer technologies for efficient and sustainable agribusiness. Miniaturized palm-sized drones can act as flexible smart sensors inspecting crops, looking for early signs of potential pest outbreaking. However, achieving such an ambitious goal requires hardware-software codesign to develop accurate deep learning (DL) detection models while keeping memory and computational needs under an ultra-tight budget, i.e., a few MB on-chip memory and a few 100s mW power envelope. This work presents a novel vertically integrated solution featuring two ultra-low power System-on-Chips (SoCs), i.e., the dual-core STM32H74 and a multi-core GWT GAP9, running two State-of-the-Art DL models for detecting the Popillia japonica bug. We fine-tune both models for our image-based detection task, quantize them in 8-bit integers, and deploy them on the two SoCs. On the STM32H74, we deploy a FOMO-MobileNetV2 model, achieving a mean average precision (mAP) of 0.66 and running at 16.1 frame/s within 498 mW. While on the GAP9 SoC, we deploy a more complex SSDLite-MobileNetV3, which scores an mAP of 0.79 and peaks at 6.8 frame/s within 33 mW. Compared to a top-notch RetinaNet-ResNet101-FPN full-precision baseline, which requires 14.9x more memory and 300x more operations per inference, our best model drops only 15\% in mAP, paving the way toward autonomous palm-sized drones capable of lightweight and precise pest detection.

Generative artificial intelligence has the potential to both exacerbate and ameliorate existing socioeconomic inequalities. In this article, we provide a state-of-the-art interdisciplinary overview of the potential impacts of generative AI on (mis)information and three information-intensive domains: work, education, and healthcare. Our goal is to highlight how generative AI could worsen existing inequalities while illuminating how AI may help mitigate pervasive social problems. In the information domain, generative AI can democratize content creation and access, but may dramatically expand the production and proliferation of misinformation. In the workplace, it can boost productivity and create new jobs, but the benefits will likely be distributed unevenly. In education, it offers personalized learning, but may widen the digital divide. In healthcare, it might improve diagnostics and accessibility, but could deepen pre-existing inequalities. In each section we cover a specific topic, evaluate existing research, identify critical gaps, and recommend research directions, including explicit trade-offs that complicate the derivation of a priori hypotheses. We conclude with a section highlighting the role of policymaking to maximize generative AI's potential to reduce inequalities while mitigating its harmful effects. We discuss strengths and weaknesses of existing policy frameworks in the European Union, the United States, and the United Kingdom, observing that each fails to fully confront the socioeconomic challenges we have identified. We propose several concrete policies that could promote shared prosperity through the advancement of generative AI. This article emphasizes the need for interdisciplinary collaborations to understand and address the complex challenges of generative AI., Comment: PNAS Nexus, in press

Dynamical Casimir effect (DCE) and cosmological particle creation (CPC) share the same underlying physical mechanism, that of parametric amplification of vacuum fluctuations in the quantum field by an expanding universe or by a fast moving boundary. Backreaction of cosmological particle creation at the Planck time has been shown to play a significant role in the isotropization and homogenization of the early universe. Understanding the backreaction effects of quantum field processes in DCE is the goal of this work. We present analyses of quantum field processes in two model systems: in 1+1D, a ring with time-dependent radius, and in 3+1D, a symmetric rectangular conducting box with one moving side. In both cases the time-dependence of the radius or the length is determined solely by the backreaction of particle creation and related effects, there is no external agent. We find that for 1+1D, the only quantum field effect due to the trace anomaly tends to accelerate the contraction of the ring over and above that due to the attractive force in the static Casimir effect. For the rectangular box the expansion or contraction is slowed down compared to that due to the static Casimir effect. Our findings comply with what is known as the quantum Lenz law, found in cosmological backreaction problems: the backreaction works in the direction of opposing further changes, which means the suppression of particle creation and a slow down of the system dynamics. In conclusion we suggest two related classes of problems of theoretical significance for further investigations., Comment: 19 pages, 3 figures

We adopt an open quantum system approach to study the effects of the back-reaction from a quantum field onto the dynamics of a moving mirror. We describe the coupling between the mirror and the field by using a microscopic model from which the dielectric response of the mirror is obtained from first principles. Using second-order perturbation theory, we derive the master equation governing the mechanical motion of the mirror. Our analysis reveals that the mirror experiences coloured noise and non-local dissipation, which originate from the emission of particle pairs via the dynamical Casimir effect. We show that the noise and dissipation kernels, that enter in the definition of the time-dependent coefficients of the master equation, are related by fluctuation-dissipation relations., Comment: 16 pages, 2 figures. Submitted to Journal of Physics: Photonics, as part of Emerging Leaders 2023 Collection

We review several aspects related to the confinement of a massless scalar field in a cavity with a movable conducting wall of finite mass, free to move around its equilibrium position to which it is bound by a harmonic potential, and whose mechanical degrees of freedom are described quantum mechanically. This system, for small displacements of the movable wall from its equilibrium position, can be described by an effective interaction Hamiltonian between the field and the mirror, quadratic in the field operators and linear in the mirror operators. In the interacting, i.e. dressed, ground state, we first consider local field observables such as the field energy density: we evaluate changes of the field energy density in the cavity with the movable wall with respect to the case of a fixed wall, and corrections to the usual Casimir forces between the two walls. We then investigate the case of two one-dimensional cavities separated by a movable wall of finite mass, with two massless scalar fields defined in the two cavities. We show that in this case correlations between the squared fields in the two cavities exist, mediated by the movable wall, at variance with the fixed-wall case., Comment: 7 pages, Proceedings of the DICE 2022 Conference, Castiglioncello, Italy

Conditioning image generation on specific features of the desired output is a key ingredient of modern generative models. However, existing approaches lack a general and unified way of representing structural and semantic conditioning at diverse granularity levels. This paper explores a novel method to condition image generation, based on object-centric relational representations. In particular, we propose a methodology to condition the generation of objects in an image on the attributed graph representing their structure and the associated semantic information. We show that such architectural biases entail properties that facilitate the manipulation and conditioning of the generative process and allow for regularizing the training procedure. The proposed conditioning framework is implemented by means of a neural network that learns to generate a 2D, multi-channel, layout mask of the objects, which can be used as a soft inductive bias in the downstream generative task. To do so, we leverage both 2D and graph convolutional operators. We also propose a novel benchmark for image generation consisting of a synthetic dataset of images paired with their relational representation. Empirical results show that the proposed approach compares favorably against relevant baselines., Comment: Accepted at TMLR

The competition between shape and perpendicular magnetic anisotropies (PMA) in magnetic thin films gives rise to unusual magnetic behaviors. In ferromagnetic films with moderate PMA the magnetic domain configuration transitions from planar to stripe-like domains above a critical thickness, $t_c$. In this article, we present a detailed study of the magnetization switching mechanism in FePt thin films, where this phenomenon is observed. Using micromagnetic simulations and experiments, we found that below $t_c$ the reversal mechanism is well described by the two-phase model while above this thickness the magnetization within each stripe reverses by coherent rotation. We also analyzed the PMA and its temperature dependence, probing that substrate-induced strains are responsible for the abnormal coercive field behavior observed for FePt films with $t>t_c$., Comment: 7 pages, 13 figures

Magnetic transition metal chalcogenides form an emerging platform for exploring spin-orbit driven Berry phase phenomena owing to the nontrivial interplay between topology and magnetism. Here we show that the anomalous Hall effect in pristine Cr2Te3 thin films manifests a unique temperature-dependent sign reversal at nonzero magnetization, resulting from the momentum-space Berry curvature as established by first-principles simulations. The sign change is strain tunable, enabled by the sharp and well-defined substrate/film interface in the quasi-two-dimensional Cr2Te3 epitaxial films, revealed by scanning transmission electron microscopy and depth-sensitive polarized neutron reflectometry. This Berry phase effect further introduces hump-shaped Hall peaks in pristine Cr2Te3 near the coercive field during the magnetization switching process, owing to the presence of strain-modulated magnetic domains. The versatile interface tunability of Berry curvature in Cr2Te3 thin films offers new opportunities for topological electronics., Comment: Main: 9 pages, 5 figures; SI: 5 pages, 9 figures

We theoretically propose an atomic Bose-Einstein condensate as an analog model of back-reaction effects during the pre-heating stage of early Universe. In particular, we address the out-of-equilibrium dynamics where the initially excited inflaton field decays by parametrically exciting the matter fields. We consider a two-dimensional, ring-shaped BEC under a tight transverse confinement whose transverse breathing mode and the Goldstone and dipole excitation branches simulate the inflaton and quantum matter fields, respectively. A strong excitation of the breathing mode leads to an exponentially-growing emission of dipole and Goldstone excitations via parametric pair creation: our numerical simulations of the BEC dynamics show how the associated back-reaction effect not only results in an effective friction of the breathing mode but also in a quick loss of longitudinal spatial coherence of the initially in-phase excitations. Implications of this result on the validity of the usual semiclassical description of back-reaction are finally discussed., Comment: 6 pages, 3 figures; comments are welcome